Does
the risk of false positive results outweigh the benefit of preventing a small number of deaths from breast cancer?
If a kitten is under 16 weeks of age and tests positive for FeLV, a re-test is recommended 3 - 4 weeks later due to the increased
risk of a false positive result in young kittens.
Not exact matches
Specifically, the task force says the «harms and costs
of false -
positive results, over diagnosis and overtreatment» outweigh any «significant reductions in the relative
risk of death from breast cancer.»
Used in conjunction with mammography, imaging based on nuclear medicine is currently being used as a successful secondary screening alongside mammography to reduce the number
of false positive results in women with dense breasts and at higher
risk for developing breast cancer.
(Scientists can increase the technique's sensitivity, but that raises the
risk of false -
positive results.)
After adjusting for common factors that influence breast cancer
risk, Henderson and colleagues found that women whose mammograms were classified as
false -
positive who were referred for additional imaging had a 39 percent increased chance
of developing subsequent breast cancer during the 10 - year follow - up period, compared with women with a true - negative
result.
«Our finding that breast cancer
risk remains elevated up to 10 years after the
false -
positive result suggests that the radiologist observed suspicious findings on mammograms that are a marker
of future cancer
risk,» said the study's lead author, Louise M. Henderson, PhD, a UNC Lineberger member and an assistant professor
of radiology at the UNC School
of Medicine.
Women with denser breasts tend to be younger, healthier women, which means healthier women are actually at an increased
risk of getting a
false result — either a
false positive or
false negative.
In healthy, low -
risk populations FIV is quite uncommon, and this leads to an increase in the relative number
of false positive results.
Plus, another unique feature is that property height (in relation to flood
risk) is included within the automated
risk model
resulting in fewer «
false positives» and a more accurate assessment
of genuine
risk.